SISTEM KONTROL TRUCK BACKER-UPPER MENGGUNAKAN JARINGAN NEURAL

Abstract

In this growing technology modern times, mostly encountered all things that are computerization oriented. Based on that, things that initially related to dynamic system and needs mathematical modeling is considered very difficult to be developed with existing methods manually. The large scope of dimensions on decision making and many other complex things caused this dynamic system meets various types of difficulty and needs a new control system which the linear one was not able to handle that complex things. One way to reach the idea of developing a new control system that can facilitate human work and mathematical modeling is to build an ‘intelligence’ factor in the control system, which is Neural Network. This ‘intelligence’ system will be applied to a control system that called Truck Backer-Upper, which is required some calculation to know how to make a truck can move backwards to park its truck to the loading dock from certain position in an area. This neural network controlling system is chosen using Backpropagation with Binary Sigmoid as its activation function and using feedforward phase on its implementation. The goal of this controlling system is resulting the right steering angle in every step of the moving truck from the first position until its target. In implementation, the final position of the truck in the loading dock is nearly perfect. The accuracy level from 70 data samples for each variable is x = 99,770% ; y = 99,061% ; dan φ = 99,986%. From these implementations, it is proven that neural controller can be used for adjusting system.